The subject matter discussed in the background section should not be assumed to be prior art merely as a result of its mention in the background section. Similarly, a problem mentioned in the background section or associated with the subject matter of the background section should not be assumed to have been previously recognized in the prior art. The subject matter in the background section merely represents different approaches, which in and of themselves may also correspond to implementations of the claimed inventions.
The technology disclosed relates to enhancing trust for person-related data sources by tracking person-related sources using trust objects that hold trust metadata. In particular, it relates to generating trust-enhanced data by appending trust metadata to social media content and other business-to-business entities, and further using the trust-enhanced data to develop social engagement models based on customer preferences. The trust metadata described includes names, interface categories and origins of the person-related data sources along with customer engagement preferences and connection types.
The increasing prevalence of businesses using electronic media to communicate with customers has triggered enactment of several regulations governing electronic marketing. These regulations set rules for use of person-related data sources and customer engagement practices, which must be abided by marketers. With marketing regulations varying by regions and corporations, efficiently maintaining highly compliant data is a problem that yet remains to be solved.
Furthermore, suppliers of person-related data have the daunting challenge to conform to changing customer engagement preferences. Existing methodologies for constantly modifying contact lists based on customer norms are extremely cumbersome as they require designated personnel to make the modifications.
Accordingly, it is desirable to provide systems and methods that offer a flexible approach to automatic compliance with changing customer preferences and regulations governing electronic marketing.
An opportunity arises to provide customer engagement models based on customer sentiments that: filter contact lists at corporate and campaign levels; efficiently identify non-compliant data; and automatically remove or replace non-compliant data. Increased customer adoption, more effective customer interactions, and higher overall customer satisfaction and retention may result.